from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HpMatchReporting(other_library="sklearnex", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 0.024 | 100000 | 1000 | 100 | 2.153970 | 0.152208 | NaN | 0.000371 | 0.002154 | brute | -1 | 1 | 0.663 | 0.220784 | 0.005899 | 0.687 | 9.756003 | 9.759485 |
| 4 | KNeighborsClassifier_brute_force | predict | 0.015 | 100000 | 1000 | 100 | 3.287839 | 0.092061 | NaN | 0.000243 | 0.003288 | brute | -1 | 5 | 0.757 | 0.214187 | 0.001486 | 0.742 | 15.350334 | 15.350704 |
| 7 | KNeighborsClassifier_brute_force | predict | 0.007 | 100000 | 1000 | 100 | 2.300400 | 0.013344 | NaN | 0.000348 | 0.002300 | brute | 1 | 100 | 0.882 | 0.264998 | 0.003964 | 0.875 | 8.680811 | 8.681782 |
| 8 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.023044 | 0.000150 | NaN | 0.000035 | 0.023044 | brute | 1 | 100 | 1.000 | 0.008720 | 0.000197 | 0.000 | 2.642717 | 2.643391 |
| 10 | KNeighborsClassifier_brute_force | predict | 0.007 | 100000 | 1000 | 100 | 3.070885 | 0.033928 | NaN | 0.000261 | 0.003071 | brute | -1 | 100 | 0.882 | 0.262483 | 0.002708 | 0.875 | 11.699366 | 11.699989 |
| 11 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.026615 | 0.002553 | NaN | 0.000030 | 0.026615 | brute | -1 | 100 | 1.000 | 0.009241 | 0.002017 | 0.000 | 2.880136 | 2.947936 |
| 13 | KNeighborsClassifier_brute_force | predict | 0.015 | 100000 | 1000 | 100 | 2.310144 | 0.006965 | NaN | 0.000346 | 0.002310 | brute | 1 | 5 | 0.757 | 0.210848 | 0.002855 | 0.742 | 10.956463 | 10.957467 |
| 16 | KNeighborsClassifier_brute_force | predict | 0.024 | 100000 | 1000 | 100 | 1.252624 | 0.002810 | NaN | 0.000639 | 0.001253 | brute | 1 | 1 | 0.663 | 0.207930 | 0.002069 | 0.687 | 6.024242 | 6.024541 |
| 19 | KNeighborsClassifier_brute_force | predict | 0.071 | 100000 | 1000 | 2 | 1.795357 | 0.028980 | NaN | 0.000009 | 0.001795 | brute | -1 | 1 | 0.896 | 0.032455 | 0.000429 | 0.967 | 55.317854 | 55.322675 |
| 22 | KNeighborsClassifier_brute_force | predict | 0.052 | 100000 | 1000 | 2 | 2.909159 | 0.043217 | NaN | 0.000005 | 0.002909 | brute | -1 | 5 | 0.922 | 0.034749 | 0.001929 | 0.974 | 83.718749 | 83.847708 |
| 25 | KNeighborsClassifier_brute_force | predict | 0.046 | 100000 | 1000 | 2 | 2.185421 | 0.003420 | NaN | 0.000007 | 0.002185 | brute | 1 | 100 | 0.929 | 0.076490 | 0.002192 | 0.975 | 28.571147 | 28.582879 |
| 28 | KNeighborsClassifier_brute_force | predict | 0.046 | 100000 | 1000 | 2 | 3.161772 | 0.093585 | NaN | 0.000005 | 0.003162 | brute | -1 | 100 | 0.929 | 0.075084 | 0.000664 | 0.975 | 42.110040 | 42.111689 |
| 31 | KNeighborsClassifier_brute_force | predict | 0.052 | 100000 | 1000 | 2 | 2.193757 | 0.010071 | NaN | 0.000007 | 0.002194 | brute | 1 | 5 | 0.922 | 0.034004 | 0.000629 | 0.974 | 64.513876 | 64.524904 |
| 34 | KNeighborsClassifier_brute_force | predict | 0.071 | 100000 | 1000 | 2 | 1.103411 | 0.006045 | NaN | 0.000015 | 0.001103 | brute | 1 | 1 | 0.896 | 0.032155 | 0.000295 | 0.967 | 34.315759 | 34.317199 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.0 | 6.345 | 0.0 | -1 | 1 | 0.051 | 0.005 | 0.246 | 0.247 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.0 | 5.906 | 0.0 | -1 | 5 | 0.049 | 0.000 | 0.275 | 0.275 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.0 | 6.011 | 0.0 | 1 | 100 | 0.049 | 0.000 | 0.274 | 0.274 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.0 | 6.296 | 0.0 | -1 | 100 | 0.049 | 0.000 | 0.260 | 0.260 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.474 | 0.0 | 1 | 5 | 0.048 | 0.000 | 0.255 | 0.255 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.0 | 6.023 | 0.0 | 1 | 1 | 0.048 | 0.000 | 0.274 | 0.274 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.302 | 0.0 | -1 | 1 | 0.010 | 0.000 | 0.549 | 0.549 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.320 | 0.0 | -1 | 5 | 0.010 | 0.000 | 0.515 | 0.515 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.303 | 0.0 | 1 | 100 | 0.010 | 0.000 | 0.542 | 0.542 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.312 | 0.0 | -1 | 100 | 0.010 | 0.000 | 0.526 | 0.526 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.303 | 0.0 | 1 | 5 | 0.010 | 0.000 | 0.539 | 0.540 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.302 | 0.0 | 1 | 1 | 0.010 | 0.000 | 0.543 | 0.543 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.154 | 0.152 | 0.000 | 0.002 | -1 | 1 | 0.221 | 0.006 | 9.756 | 9.759 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.027 | 0.002 | 0.000 | 0.027 | -1 | 1 | 0.009 | 0.000 | 3.049 | 3.050 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.288 | 0.092 | 0.000 | 0.003 | -1 | 5 | 0.214 | 0.001 | 15.350 | 15.351 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.028 | 0.004 | 0.000 | 0.028 | -1 | 5 | 0.008 | 0.000 | 3.326 | 3.327 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.300 | 0.013 | 0.000 | 0.002 | 1 | 100 | 0.265 | 0.004 | 8.681 | 8.682 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.000 | 0.000 | 0.023 | 1 | 100 | 0.009 | 0.000 | 2.643 | 2.643 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.071 | 0.034 | 0.000 | 0.003 | -1 | 100 | 0.262 | 0.003 | 11.699 | 11.700 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.027 | 0.003 | 0.000 | 0.027 | -1 | 100 | 0.009 | 0.002 | 2.880 | 2.948 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.310 | 0.007 | 0.000 | 0.002 | 1 | 5 | 0.211 | 0.003 | 10.956 | 10.957 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.024 | 0.000 | 0.000 | 0.024 | 1 | 5 | 0.008 | 0.000 | 2.879 | 2.882 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.253 | 0.003 | 0.001 | 0.001 | 1 | 1 | 0.208 | 0.002 | 6.024 | 6.025 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.001 | 0.000 | 0.023 | 1 | 1 | 0.008 | 0.000 | 2.803 | 2.804 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.795 | 0.029 | 0.000 | 0.002 | -1 | 1 | 0.032 | 0.000 | 55.318 | 55.323 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.004 | 0.000 | 0.006 | -1 | 1 | 0.001 | 0.000 | 8.193 | 8.221 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.909 | 0.043 | 0.000 | 0.003 | -1 | 5 | 0.035 | 0.002 | 83.719 | 83.848 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.013 | 0.004 | 0.000 | 0.013 | -1 | 5 | 0.001 | 0.000 | 17.248 | 17.295 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.185 | 0.003 | 0.000 | 0.002 | 1 | 100 | 0.076 | 0.002 | 28.571 | 28.583 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | 0.000 | 0.004 | 1 | 100 | 0.001 | 0.000 | 4.298 | 4.305 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 3.162 | 0.094 | 0.000 | 0.003 | -1 | 100 | 0.075 | 0.001 | 42.110 | 42.112 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.010 | 0.005 | 0.000 | 0.010 | -1 | 100 | 0.001 | 0.000 | 10.183 | 10.290 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.194 | 0.010 | 0.000 | 0.002 | 1 | 5 | 0.034 | 0.001 | 64.514 | 64.525 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | 0.000 | 0.004 | 1 | 5 | 0.001 | 0.000 | 4.754 | 4.767 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.103 | 0.006 | 0.000 | 0.001 | 1 | 1 | 0.032 | 0.000 | 34.316 | 34.317 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 0.001 | 0.000 | 2.670 | 2.676 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 0.019 | 1000000 | 1000 | 10 | 0.862342 | 1.047025 | NaN | 0.000093 | 0.000862 | kd_tree | -1 | 1 | 0.929 | 0.114904 | 0.002498 | 0.910 | 7.504871 | 7.506645 |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.005 | 1000000 | 1000 | 10 | 1.141153 | 0.413375 | NaN | 0.000070 | 0.001141 | kd_tree | -1 | 5 | 0.946 | 0.206937 | 0.002263 | 0.941 | 5.514502 | 5.514831 |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.011 | 1000000 | 1000 | 10 | 5.865079 | 0.462938 | NaN | 0.000014 | 0.005865 | kd_tree | 1 | 100 | 0.951 | 0.629273 | 0.012421 | 0.940 | 9.320398 | 9.322213 |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.011 | 1000000 | 1000 | 10 | 3.428704 | 0.220996 | NaN | 0.000023 | 0.003429 | kd_tree | -1 | 100 | 0.951 | 0.619292 | 0.006916 | 0.940 | 5.536494 | 5.536840 |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.005 | 1000000 | 1000 | 10 | 1.768106 | 0.119270 | NaN | 0.000045 | 0.001768 | kd_tree | 1 | 5 | 0.946 | 0.210532 | 0.004980 | 0.941 | 8.398288 | 8.400638 |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.019 | 1000000 | 1000 | 10 | 0.895234 | 0.172745 | NaN | 0.000089 | 0.000895 | kd_tree | 1 | 1 | 0.929 | 0.116658 | 0.013346 | 0.910 | 7.673978 | 7.724035 |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.012 | 1000 | 1000 | 2 | 0.032551 | 0.018237 | NaN | 0.000492 | 0.000033 | kd_tree | -1 | 1 | 0.891 | 0.000484 | 0.000080 | 0.879 | 67.246767 | 68.153671 |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.006 | 1000 | 1000 | 2 | 0.027045 | 0.001408 | NaN | 0.000592 | 0.000027 | kd_tree | -1 | 5 | 0.911 | 0.000757 | 0.000033 | 0.905 | 35.735502 | 35.768460 |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.023 | 1000 | 1000 | 2 | 0.040791 | 0.007561 | NaN | 0.000392 | 0.000041 | kd_tree | 1 | 100 | 0.894 | 0.005784 | 0.000939 | 0.917 | 7.052774 | 7.145113 |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.023 | 1000 | 1000 | 2 | 0.044051 | 0.005763 | NaN | 0.000363 | 0.000044 | kd_tree | -1 | 100 | 0.894 | 0.006336 | 0.001898 | 0.917 | 6.952703 | 7.258124 |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.006 | 1000 | 1000 | 2 | 0.023866 | 0.000403 | NaN | 0.000670 | 0.000024 | kd_tree | 1 | 5 | 0.911 | 0.000758 | 0.000033 | 0.905 | 31.485393 | 31.514429 |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.012 | 1000 | 1000 | 2 | 0.021472 | 0.000124 | NaN | 0.000745 | 0.000021 | kd_tree | 1 | 1 | 0.891 | 0.000450 | 0.000037 | 0.879 | 47.742564 | 47.906895 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.210 | 0.015 | 0.025 | 0.0 | -1 | 1 | 0.845 | 0.035 | 3.797 | 3.801 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.739 | 0.165 | 0.017 | 0.0 | -1 | 5 | 0.828 | 0.007 | 5.723 | 5.723 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.349 | 0.040 | 0.018 | 0.0 | 1 | 100 | 0.797 | 0.009 | 5.457 | 5.457 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.346 | 0.032 | 0.018 | 0.0 | -1 | 100 | 0.830 | 0.007 | 5.235 | 5.235 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.612 | 0.078 | 0.017 | 0.0 | 1 | 5 | 0.797 | 0.010 | 5.785 | 5.786 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.611 | 0.090 | 0.017 | 0.0 | 1 | 1 | 0.831 | 0.017 | 5.546 | 5.547 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | 0.018 | 0.0 | -1 | 1 | 0.004 | 0.002 | 0.250 | 0.291 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.025 | 0.0 | -1 | 5 | 0.001 | 0.001 | 0.522 | 0.580 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.026 | 0.0 | 1 | 100 | 0.001 | 0.001 | 0.480 | 0.535 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.026 | 0.0 | -1 | 100 | 0.001 | 0.000 | 0.475 | 0.495 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.026 | 0.0 | 1 | 5 | 0.001 | 0.000 | 0.574 | 0.574 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.026 | 0.0 | 1 | 1 | 0.001 | 0.000 | 0.594 | 0.595 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.862 | 1.047 | 0.000 | 0.001 | -1 | 1 | 0.115 | 0.002 | 7.505 | 7.507 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 11.125 | 11.527 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.141 | 0.413 | 0.000 | 0.001 | -1 | 5 | 0.207 | 0.002 | 5.515 | 5.515 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.000 | 0.000 | 0.004 | -1 | 5 | 0.000 | 0.000 | 7.948 | 8.292 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.865 | 0.463 | 0.000 | 0.006 | 1 | 100 | 0.629 | 0.012 | 9.320 | 9.322 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.001 | 0.000 | 0.004 | 1 | 100 | 0.001 | 0.000 | 4.439 | 4.564 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.429 | 0.221 | 0.000 | 0.003 | -1 | 100 | 0.619 | 0.007 | 5.536 | 5.537 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.007 | 0.001 | 0.000 | 0.007 | -1 | 100 | 0.001 | 0.000 | 7.821 | 8.074 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.768 | 0.119 | 0.000 | 0.002 | 1 | 5 | 0.211 | 0.005 | 8.398 | 8.401 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 5 | 0.001 | 0.000 | 3.686 | 3.784 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.895 | 0.173 | 0.000 | 0.001 | 1 | 1 | 0.117 | 0.013 | 7.674 | 7.724 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 3.180 | 3.291 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.033 | 0.018 | 0.000 | 0.000 | -1 | 1 | 0.000 | 0.000 | 67.247 | 68.154 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 35.614 | 37.240 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.027 | 0.001 | 0.001 | 0.000 | -1 | 5 | 0.001 | 0.000 | 35.736 | 35.768 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 0.000 | 0.000 | 22.703 | 23.676 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.041 | 0.008 | 0.000 | 0.000 | 1 | 100 | 0.006 | 0.001 | 7.053 | 7.145 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 0.000 | 0.000 | 4.630 | 4.988 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.044 | 0.006 | 0.000 | 0.000 | -1 | 100 | 0.006 | 0.002 | 6.953 | 7.258 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.002 | 0.000 | 0.003 | -1 | 100 | 0.000 | 0.000 | 32.426 | 34.088 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.024 | 0.000 | 0.001 | 0.000 | 1 | 5 | 0.001 | 0.000 | 31.485 | 31.514 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 0.000 | 0.000 | 6.982 | 7.324 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.021 | 0.000 | 0.001 | 0.000 | 1 | 1 | 0.000 | 0.000 | 47.743 | 47.907 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 6.726 | 7.037 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.603 | 0.081 | 30 | 0.027 | 0.0 | random | 0.504 | 0.043 | 1.195 | 1.200 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.665 | 0.017 | 30 | 0.024 | 0.0 | k-means++ | 0.528 | 0.032 | 1.259 | 1.261 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 6.605 | 0.222 | 30 | 0.121 | 0.0 | random | 3.074 | 0.043 | 2.148 | 2.149 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 6.817 | 0.052 | 30 | 0.117 | 0.0 | k-means++ | 3.219 | 0.051 | 2.118 | 2.118 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.001 | 30 | 0.007 | 0.000 | random | 0.0 | 0.0 | 9.970 | 13.715 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | random | 0.0 | 0.0 | 9.167 | 14.054 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.000 | 30 | 0.010 | 0.000 | k-means++ | 0.0 | 0.0 | 9.435 | 10.328 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | k-means++ | 0.0 | 0.0 | 13.086 | 14.272 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.003 | 0.001 | 30 | 0.317 | 0.000 | random | 0.0 | 0.0 | 8.921 | 9.437 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.001 | 0.002 | random | 0.0 | 0.0 | 11.591 | 11.872 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.395 | 0.000 | k-means++ | 0.0 | 0.0 | 6.171 | 6.367 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | k-means++ | 0.0 | 0.0 | 12.328 | 12.491 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | diff_adjusted_rand_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | init | max_iter | n_clusters | n_init | tol | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 0.001090 | 10000 | 1000 | 2 | 0.002274 | 0.000144 | 20 | 0.007036 | 0.000002 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.000126 | 0.000559 | 0.000042 | -0.000965 | 4.066435 | 4.078042 |
| 4 | KMeans_short | predict | 0.001995 | 10000 | 1000 | 2 | 0.002095 | 0.000093 | 20 | 0.007636 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.001245 | 0.000579 | 0.000034 | -0.000750 | 3.617104 | 3.623289 |
| 7 | KMeans_short | predict | 0.015034 | 10000 | 1000 | 100 | 0.002918 | 0.000122 | 20 | 0.274130 | 0.000003 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.278733 | 0.001217 | 0.000117 | 0.293767 | 2.398745 | 2.409838 |
| 10 | KMeans_short | predict | 0.060044 | 10000 | 1000 | 100 | 0.003082 | 0.000184 | 20 | 0.259563 | 0.000003 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.317011 | 0.001163 | 0.000085 | 0.256968 | 2.650903 | 2.657993 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.096 | 0.001 | 20 | 0.002 | 0.0 | random | 0.034 | 0.002 | 2.859 | 2.865 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.268 | 0.003 | 20 | 0.001 | 0.0 | k-means++ | 0.099 | 0.000 | 2.712 | 2.712 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.247 | 0.005 | 20 | 0.032 | 0.0 | random | 0.136 | 0.001 | 1.811 | 1.811 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 0.708 | 0.009 | 20 | 0.011 | 0.0 | k-means++ | 0.386 | 0.007 | 1.832 | 1.832 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.000 | 20 | 0.007 | 0.000 | random | 0.001 | 0.0 | 4.066 | 4.078 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | random | 0.000 | 0.0 | 13.312 | 13.713 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.000 | 20 | 0.008 | 0.000 | k-means++ | 0.001 | 0.0 | 3.617 | 3.623 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.001 | 20 | 0.000 | 0.002 | k-means++ | 0.000 | 0.0 | 15.272 | 15.665 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.000 | 20 | 0.274 | 0.000 | random | 0.001 | 0.0 | 2.399 | 2.410 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | random | 0.000 | 0.0 | 10.276 | 10.394 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.000 | 20 | 0.260 | 0.000 | k-means++ | 0.001 | 0.0 | 2.651 | 2.658 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | k-means++ | 0.000 | 0.0 | 9.649 | 9.800 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 0.01 | 1000000 | 1000 | 100 | 0.000436 | 0.000444 | [20] | 1.835441 | 4.358625e-07 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.56 | 0.000786 | 0.001236 | 0.55 | 0.554419 | 1.032939 |
| 4 | LogisticRegression | predict | 0.07 | 1000 | 100 | 10000 | 0.001962 | 0.000180 | [26] | 4.078155 | 1.961671e-05 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.35 | 0.006310 | 0.000652 | 0.28 | 0.310900 | 0.312555 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 12.023 | 0.367 | [20] | 0.067 | 0.000 | 2.129 | 0.031 | 5.647 | 5.647 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 1.020 | 0.650 | [26] | 0.078 | 0.001 | 0.822 | 0.036 | 1.240 | 1.242 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | [20] | 1.835 | 0.0 | 0.001 | 0.001 | 0.554 | 1.033 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | [20] | 0.013 | 0.0 | 0.000 | 0.000 | 0.382 | 0.388 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.002 | 0.0 | [26] | 4.078 | 0.0 | 0.006 | 0.001 | 0.311 | 0.313 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | [26] | 0.894 | 0.0 | 0.002 | 0.000 | 0.050 | 0.050 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | diff_r2_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | r2_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | r2_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 0.039624 | 1000 | 1000 | 10000 | 0.010489 | 0.000301 | NaN | 7.627313 | 0.00001 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | 0.082567 | 0.017926 | 0.000491 | 0.122191 | 0.585093 | 0.585312 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.202 | 0.006 | 0.396 | 0.0 | 0.210 | 0.001 | 0.964 | 0.964 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.241 | 0.076 | 0.644 | 0.0 | 0.366 | 0.290 | 3.392 | 4.327 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.01 | 0.0 | 7.627 | 0.0 | 0.018 | 0.0 | 0.585 | 0.585 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.00 | 0.0 | 1.127 | 0.0 | 0.000 | 0.0 | 0.588 | 0.614 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.00 | 0.0 | 4.981 | 0.0 | 0.000 | 0.0 | 0.506 | 0.684 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.00 | 0.0 | 0.015 | 0.0 | 0.000 | 0.0 | 0.572 | 0.602 | See | See |